DBMS > Amazon Redshift vs. HEAVY.AI vs. JanusGraph vs. NuoDB vs. Qdrant

System Properties Comparison Amazon Redshift vs. HEAVY.AI vs. JanusGraph vs. NuoDB vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

NuoDB is a webscale distributed database that supports SQL and ACID transactions

A high-performance vector database with neural network or semantic-based matching

Primary database model

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.87
Rank	#201	Overall
	#94	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

aws.amazon.com/redshift

github.com/heavyai/heavydb
www.heavy.ai

janusgraph.org

www.3ds.com/nuodb-distributed-sql-database

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.aws.amazon.com/redshift

docs.heavy.ai

docs.janusgraph.org

doc.nuodb.com

qdrant.tech/documentation

Developer

Amazon (based on PostgreSQL)

HEAVY.AI, Inc.

Linux Foundation; originally developed as Titan by Aurelius

Dassault Systèmes

originally NuoDB, Inc.

Qdrant

Initial release

2012

2016

2017

2013

2021

Current release

5.10, January 2022

1.0.0, October 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

limited edition free

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

Java

C++

Rust

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

restricted

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/Thrift
Python

Clojure
Java
Python

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Managed transparently by NuoDB

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Temporary table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

Standard SQL roles/ privileges, Administrative Users

Key-based authentication

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